Data-themed articles, essays, and studies

Trump v. Analysis

After ceding leadership of the free world to Germany, Canada, and possibly California, our president returned home to 1) take swipes at the numerous governmental organs investigating his administration; 2) cede leadership in climate control to a combination of Europe and China; and 3) propose a new healthcare rule that would deny birth control coverage to many women. Proving, as if we needed more poof, that it’s easier to destroy than to create – it always has been.

Item (3) was interesting not only for its consequences, but because it exposed a recurring fallacy. If you read through the New York Times article, you’ll find that the the new rule was defended, in part, as follows: a statistical study examining the link between birth control and reduced rates of pregnancy failed to establish a causal connection between the two. Ergo, it should be easier to claim moral exemptions for covering birth control in health insurance policies.

I am not sure why the administration felt compelled to make a bad scientific argument for what is plainly a political action. But they did, perhaps trying to refute the charge they are inept in nearly every technical endeavor. Well, this will not help their cause.

First. The study didn’t establish causation, but that wasn’t its job. Statistical studies by themselves do not establish causation. Statistics lets us know if A and B are probably the same, or different, or occur together, or don’t. That’s correlation, but not causation. Causation lies in the realm of extra-statistical reasoning. For example, with statistics I might associate downed tree limbs with wind storms. Strictly speaking, that’s all I know at this point – a falling tree limb might create wind for all I know (and it does, a little…). It takes atmospheric physics to explain the wind forces necessary to fell an oak, and from there to establish (probable) causation.

Second. The cited study wasn’t conducted under controlled conditions. A field study can fail to show correlation due to any number of mitigating factors. In general, the absence of a correlation does not prove there couldn’t be one. It simply means the study showed nothing – that’s it.

Third. Contraceptive device and drugs are FDA-approved, and have undergone studies under controlled conditions, showing with resounding certainty that women using contraception are far less likely to become pregnant. Strictly speaking that still doesn’t prove causation, but an alternative explanation would really be from The Twilight Zone.

Fourth. Unconstrained optimization on empirical models (even if it had been performed correctly) is rarely the basis for a correct decision. If we optimize the cost of contraceptives to the government, and we may very well incur other costs elsewhere, later on.

This was a political decision, appealing to those not wishing to provide birth control for moral reasons. It can and should be judged by voters on those grounds. The smokescreen of a pseudo-scientific argument simply reinforces suspicions about the administration in the technical community. It would be best to forthrightly state the actual reason for the decision, and let it go at that. But that just isn’t their style – they’ll probably try science again, with similar results. I can’t wait to hear the reasons for leaving the climate treaty….